Olaris Global Panel (OGP): A Highly Accurate and Reproducible Triple Quadrupole Mass Spectrometry-Based Metabolomics Method for Clinical Biomarker Discovery

Mass spectrometry (MS)-based clinical metabolomics is very promising for the discovery of new biomarkers and diagnostics. However, poor data accuracy and reproducibility limit its true potential, especially when performing data analysis across multiple sample sets. While high-resolution mass spectrometry has gained considerable popularity for discovery metabolomics, triple quadrupole (QqQ) instruments offer several benefits for the measurement of known metabolites in clinical samples. These benefits include high sensitivity and a wide dynamic range. Here, we present the Olaris Global Panel (OGP), a HILIC LC-QqQ MS method for the comprehensive analysis of ~250 metabolites from all major metabolic pathways in clinical samples. For the development of this method, multiple HILIC columns and mobile phase conditions were compared, the robustness of the leading LC method assessed, and MS acquisition settings optimized for optimal data quality. Next, the effect of U-13C metabolite yeast extract spike-ins was assessed based on data accuracy and precision. The use of these U-13C-metabolites as internal standards improved the goodness of fit to a linear calibration curve from r2 < 0.75 for raw data to >0.90 for most metabolites across the entire clinical concentration range of urine samples. Median within-batch CVs for all metabolite ratios to internal standards were consistently lower than 7% and less than 10% across batches that were acquired over a six-month period. Finally, the robustness of the OGP method, and its ability to identify biomarkers, was confirmed using a large sample set.

Multiomics Approach Reveals Serum Biomarker Candidates for Congenital Zika Syndrome

The Zika virus (ZIKV) can be vertically transmitted, causing congenital Zika syndrome (CZS) in fetuses. ZIKV infection in early gestational trimesters increases the chances of developing CZS. This syndrome involves several pathologies with a complex diagnosis. In this work, we aim to identify biological processes and molecular pathways related to CZS and propose a series of putative protein and metabolite biomarkers for CZS prognosis in early pregnancy trimesters. We analyzed serum samples of healthy pregnant women and ZIKV-infected pregnant women bearing nonmicrocephalic and microcephalic fetuses. A total of 1090 proteins and 512 metabolites were identified by bottom-up proteomics and untargeted metabolomics, respectively. Univariate and multivariate statistical approaches were applied to find CZS differentially abundant proteins (DAP) and metabolites (DAM). Enrichment analysis (i.e., biological processes and molecular pathways) of the DAP and the DAM allowed us to identify the ECM organization and proteoglycans, amino acid metabolism, and arachidonic acid metabolism as CZS signatures. Five proteins and four metabolites were selected as CZS biomarker candidates. Serum multiomics analysis led us to propose nine putative biomarkers for CZS prognosis with high sensitivity and specificity.

Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Integrative Metabolomics and Proteomics Allow the Global Intracellular Characterization of Bacillus subtilis Cells and Spores

Reliable and comprehensive multi-omics analysis is essential for researchers to understand and explore complex biological systems more completely. Bacillus subtilis (B. subtilis) is a model organism for Gram-positive spore-forming bacteria, and in-depth insight into the physiology and molecular basis of spore formation and germination in this organism requires advanced multilayer molecular data sets generated from the same sample. In this study, we evaluated two monophasic methods for polar and nonpolar compound extraction (acetonitrile/methanol/water; isopropanol/water, and 60% ethanol) and two biphasic methods (chloroform/methanol/water, and methyl tert-butyl ether/methanol/water) on coefficients of variation of analytes, identified metabolite composition, and the quality of proteomics profiles. The 60% EtOH protocol proved to be the easiest in sample processing and was more amenable to automation. Collectively, we annotated 505 and 484 metabolites and identified 1665 and 1562 proteins in B. subtilis vegetative cells and spores, respectively. We also show differences between vegetative cells and spores from a multi-omics perspective and demonstrate that an integrative multi-omics analysis can be implemented from one sample using the 60% EtOH protocol. The results obtained by the 60% EtOH protocol provide comprehensive insight into differences in the metabolic and protein makeup of B. subtilis vegetative cells and spores.

Analysis of Relationships between Metabolic Changes and Selected Nutrient Intake in Women Environmentally Exposed to Arsenic

Nutrients involved in the metabolism of inorganic arsenic (iAs) may play a crucial role in mitigating the adverse health effects associated with such exposure. Consequently, the objective of this study was to analyze the association between the intake levels of nutrients involved in iAs metabolism and alterations in the metabolic profile during arsenic exposure. The study cohort comprised environmentally exposed women: WL (lower total urinary arsenic (As), n = 73) and WH (higher As, n = 73). The analysis included urinary untargeted metabolomics (conducted via liquid chromatography-mass spectrometry) and the assessment of nutrient intake involved in iAs metabolism, specifically methionine, vitamins B2, B6, and B12, folate, and zinc (based on 3-day dietary records of food and beverages). In the WL group, the intake of all analyzed nutrients exhibited a negative correlation with 5 metabolites (argininosuccinic acid, 5-hydroxy-L-tryptophan, 11-trans-LTE4, mevalonic acid, aminoadipic acid), while in the WH group, it correlated with 10 metabolites (5-hydroxy-L-tryptophan, dihyroxy-1H-indole glucuronide I, 11-trans-LTE4, isovalerylglucuronide, 18-oxocortisol, 3-hydroxydecanedioic acid, S-3-oxodecanoyl cysteamine, L-arginine, p-cresol glucuronide, thromboxane B2). Furthermore, nutrient intake demonstrated a positive association with 3 metabolites in the WL group (inosine, deoxyuridine, glutamine) and the WH group (inosine, N-acetyl-L-aspartic acid, tetrahydrodeoxycorticosterone). Altering the intake of nutrients involved in iAs metabolism could be a pivotal factor in reducing the negative impact of arsenic exposure on the human body. This study underscores the significance of maintaining adequate nutrient intake, particularly in populations exposed to arsenic.

Emergency diagnosis made easy: matrix removal and analyte enrichment from raw saliva using paper-arrow mass spectrometry

Paracetamol overdose is a leading cause of acute liver failure that can prove fatal. Establishing paracetamol concentration accurately and quickly is critical. Current detection methods are invasive, time-consuming and/or expensive. Non-invasive, rapid and cost-effective techniques are urgently required. To address this challenge, a novel approach, called Paper-Arrow Mass Spectrometry (PA-MS) has been developed. This technique combines sample collection, extraction, enrichment, separation and ionisation onto a single paper strip, and the entire analysis process, from sample to result, can be carried out in less than 10 min requiring only 2 μL of raw human saliva. PA-MS achieved a LOQ of 185 ng mL-1, mean recovery of 107 ± 7%, mean accuracy of 11 ± 8% and precision ≤5% using four concentrations, and had excellent linearity (r2 = 0.9988) in the range of 0.2-200 μg mL-1 covering the treatment concentration range, surpassing the best-in-class methods currently available for paracetamol analysis. Furthermore, from a panel of human saliva samples, inter-individual variability was found to be <10% using this approach. This technique represents a promising tool for rapid and accurate emergency diagnosis.

Optimization Strategies for Mass Spectrometry-Based Untargeted Metabolomics Analysis of Small Polar Molecules in Human Plasma

The untargeted approach to mass spectrometry-based metabolomics has a wide potential to investigate health and disease states, identify new biomarkers for diseases, and elucidate metabolic pathways. All this holds great promise for many applications in biological and chemical research. However, the complexity of instrumental parameters on advanced hybrid mass spectrometers can make the optimization of the analytical method immensely challenging. Here, we report a strategy to optimize the selected settings of a hydrophilic interaction liquid chromatography-tandem mass spectrometry method for untargeted metabolomics studies of human plasma, as a sample matrix. Specifically, we evaluated the effects of the reconstitution solvent in the sample preparation procedure, the injection volume employed, and different mass spectrometry-related operating parameters including mass range, the number of data-dependent fragmentation scans, collision energy mode, duration of dynamic exclusion time, and mass resolution settings on the metabolomics data quality and output. This study highlights key instrumental variables influencing the detection of metabolites along with suggested settings for the IQ-X tribrid system and proposes a new methodological framework to ensure increased metabolome coverage.

Simultaneously discovering the fate and biochemical effects of pharmaceuticals through untargeted metabolomics

Untargeted metabolomics is an established approach in toxicology for characterising endogenous metabolic responses to xenobiotic exposure. Detecting the xenobiotic and its biotransformation products as part of the metabolomics analysis provides an opportunity to simultaneously gain deep insights into its fate and metabolism, and to associate the internal relative dose directly with endogenous metabolic responses. This integration of untargeted exposure and response measurements into a single assay has yet to be fully demonstrated. Here we assemble a workflow to discover and analyse pharmaceutical-related measurements from routine untargeted UHPLC-MS metabolomics datasets, derived from in vivo (rat plasma and cardiac tissue, and human plasma) and in vitro (human cardiomyocytes) studies that were principally designed to investigate endogenous metabolic responses to drug exposure. Our findings clearly demonstrate how untargeted metabolomics can discover extensive biotransformation maps, temporally-changing relative systemic exposure, and direct associations of endogenous biochemical responses to the internal dose.

A rapid single-phase extraction for polar staphylococcal lipids

The lipid membrane is gaining appreciation as a critical factor in the emergence of antibiotic resistance, both for antibiotics that target lipid synthesis or the membrane directly and for cell-wall-targeting antibiotics. The methods used to study the emergence of antibiotic resistance in vitro can generate a large number of samples that may be low in volume and in cell density. As in eukaryotic/mammalian lipidomics, two-phase liquid-liquid extractions are the most commonly used approach to recover lipids from bacteria. The need to separate the lipid layer is cumbersome for high-throughput applications and can be a source of poor reproducibility or contaminant introduction. While several single-phase extractions have been proposed for serum, tissue, and eukaryotic cells, there have been far fewer efforts to adapt or develop such methods for bacteria lipidomics. Here, we describe a simple, single-phase lipid extraction method based on methanol, acetonitrile, and water-the MAW method. The merits of the MAW method are evaluated against the Bligh & Dyer (B&D) method for the recovery of the major membrane lipids (phosphatidylglycerols, diglycosyldiacylglycerols, and lysyl-phosphatidylglycerols) in the Gram-positive pathogen Staphylococcus aureus. We demonstrate that the MAW method achieves recoveries that are comparable to that of the B&D extraction (≥ 85% for PG 15:0/d₇-18:1). The benefits of the MAW method enable the detection of lipids from lower amounts of bacteria than the B&D method (0.57 vs 0.74 McFarlands for PG 32:0, respectively) and is easily scaled down to microplate volumes to facilitate high-throughput studies of bacterial lipids.

The Effects of Two Kinds of Dietary Interventions on Serum Metabolic Profiles in Haemodialysis Patients

The goal of this study was to evaluate the effects of two kinds of 24-week dietary interventions in haemodialysis patients, a traditional nutritional intervention without a meal before dialysis (HG1) and implementation of a nutritional intervention with a meal served just before dialysis (HG2), in terms of analysing the differences in the serum metabolic profiles and finding biomarkers of dietary efficacy. These studies were performed in two homogenous groups of patients (n = 35 in both groups). Among the metabolites with the highest statistical significance between HG1 and HG2 after the end of the study, 21 substances were putatively annotated, which had potential significance in both of the most relevant metabolic pathways and those related to diet. After the 24 weeks of the dietary intervention, the main differences between the metabolomic profiles in the HG2 vs. HG1 groups were related to the higher signal intensities from amino acid metabolites: indole-3-carboxaldehyde, 5-(hydroxymethyl-2-furoyl)glycine, homocitrulline, 4-(glutamylamino)butanoate, tryptophol, gamma-glutamylthreonine, and isovalerylglycine. These metabolites are intermediates in the metabolic pathways of the necessary amino acids (Trp, Tyr, Phe, Leu, Ile, Val, Liz, and amino acids of the urea cycle) and are also diet-related intermediates (4-guanidinobutanoic acid, indole-3-carboxyaldehyde, homocitrulline, and isovalerylglycine).

Evaluation of Two Simultaneous Metabolomic and Proteomic Extraction Protocols Assessed by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry

Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently-used solvent systems: chloroform/methanol and methanol-only. Whole blood samples were collected from participants (n = 6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods: (i) methanol precipitation and (ii) 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.

Derivation of metabolic point of departure using high-throughput in vitro metabolomics: investigating the importance of sampling time points on benchmark concentration values in the HepaRG cell line

Amongst omics technologies, metabolomics should have particular value in regulatory toxicology as the measurement of the molecular phenotype is the closest to traditional apical endpoints, whilst offering mechanistic insights into the biological perturbations. Despite this, the application of untargeted metabolomics for point-of-departure (POD) derivation via benchmark concentration (BMC) modelling is still a relatively unexplored area. In this study, a high-throughput workflow was applied to derive PODs associated with a chemical exposure by measuring the intracellular metabolome of the HepaRG cell line following treatment with one of four chemicals (aflatoxin B₁, benzo[a]pyrene, cyclosporin A, or rotenone), each at seven concentrations (aflatoxin B₁, benzo[a]pyrene, cyclosporin A: from 0.2048 μM to 50 μM; rotenone: from 0.04096 to 10 μM) and five sampling time points (2, 6, 12, 24 and 48 h). The study explored three approaches to derive PODs using benchmark concentration modelling applied to single features in the metabolomics datasets or annotated metabolites or lipids: (1) the 1st rank-ordered unannotated feature, (2) the 1st rank-ordered putatively annotated feature (using a recently developed HepaRG-specific library of polar metabolites and lipids), and (3) 25th rank-ordered feature, demonstrating that for three out of four chemical datasets all of these approaches led to relatively consistent BMC values, varying less than tenfold across the methods. In addition, using the 1st rank-ordered unannotated feature it was possible to investigate temporal trends in the datasets, which were shown to be chemical specific. Furthermore, a possible integration of metabolomics-driven POD derivation with the liver steatosis adverse outcome pathway (AOP) was demonstrated. The study highlights that advances in technologies enable application of in vitro metabolomics at scale; however, greater confidence in metabolite identification is required to ensure PODs are mechanistically anchored.

Metabolic Changes and Their Associations with Selected Nutrients Intake in the Group of Workers Exposed to Arsenic

Arsenic (As) exposure causes numerous adverse health effects, which can be reduced by the nutrients involved in the metabolism of iAs (inorganic As). This study was carried out on two groups of copper-smelting workers: WN, workers with a urinary total arsenic (tAs) concentration within the norm (n = 75), and WH, workers with a urinary tAs concentration above the norm (n = 41). This study aimed to analyze the association between the intake level of the nutrients involved in iAs metabolism and the signal intensity of the metabolites that were affected by iAs exposure. An untargeted metabolomics analysis was carried out on urine samples using liquid chromatography-mass spectrometry, and the intake of the nutrients was analyzed based on 3-day dietary records. Compared with the WN group, five pathways (the metabolism of amino acids, carbohydrates, glycans, vitamins, and nucleotides) with twenty-five putatively annotated metabolites were found to be increased in the WH group. In the WN group, the intake of nutrients (methionine; vitamins B2, B6, and B12; folate; and zinc) was negatively associated with six metabolites (cytosine, D-glucuronic acid, N-acetyl-D-glucosamine, pyroglutamic acid, uridine, and urocanic acid), whereas in the WH group, it was associated with five metabolites (D-glucuronic acid, L-glutamic acid, N-acetyl-D-glucosamine, N-acetylneuraminic acid, and uridine). Furthermore, in the WH group, positive associations between methionine, folate, and zinc intake and the signal intensity of succinic acid and 3-mercaptolactic acid were observed. These results highlight the need to educate the participants about the intake level of the nutrients involved in iAs metabolism and may contribute to further considerations with respect to the formulation of dietary recommendations for people exposed to iAs.

An Optimised Monophasic Faecal Extraction Method for LC-MS Analysis and Its Application in Gastrointestinal Disease

Liquid chromatography coupled with mass spectrometry (LC-MS) metabolomic approaches are widely used to investigate underlying pathogenesis of gastrointestinal disease and mechanism of action of treatments. However, there is an unmet requirement to assess faecal metabolite extraction methods for large-scale metabolomics studies. Current methods often rely on biphasic extractions using harmful halogenated solvents, making automation and large-scale studies challenging. The present study reports an optimised monophasic faecal extraction protocol that is suitable for untargeted and targeted LC-MS analyses. The impact of several experimental parameters, including sample weight, extraction solvent, cellular disruption method, and sample-to-solvent ratio, were investigated. It is suggested that a 50 mg freeze-dried faecal sample should be used in a methanol extraction (1:20) using bead beating as the means of cell disruption. This is revealed by a significant increase in number of metabolites detected, improved signal intensity, and wide metabolic coverage given by each of the above extraction parameters. Finally, we addressed the applicability of the method on faecal samples from patients with Crohn's disease (CD) and coeliac disease (CoD), two distinct chronic gastrointestinal diseases involving metabolic perturbations. Untargeted and targeted metabolomic analysis demonstrated the ability of the developed method to detect and stratify metabolites extracted from patient groups and healthy controls (HC), highlighting characteristic changes in the faecal metabolome according to disease. The method developed is, therefore, suitable for the analysis of patients with gastrointestinal disease and can be used to detect and distinguish differences in the metabolomes of CD, CoD, and HC.

Saliva metabolome alterations after acute stress

Major stress has systemic effects on the body that can have adverse consequences for physical and mental health. However, the molecular basis of these damaging effects remains incompletely understood. Here we use a longitudinal approach to characterise the acute systemic impact of major psychological stress in a pig model. We perform untargeted metabolomics on non-invasively obtained saliva samples from pigs before and 24 h after transfer to the novel physical and social environment of a slaughterhouse. The main molecular changes occurring include decreases in amino acids, B-vitamins, and amino acid-derived metabolites synthesized in B-vitamin-dependent reactions, as well as yet-unidentified metabolite features. Decreased levels of several of the identified metabolites are implicated in the pathology of human psychological disorders and neurodegenerative disease, suggesting a possible neuroprotective function. Our results provide a fingerprint of the acute effect of psychological stress on the metabolome and suggest candidate biomarkers with potential roles in stress-related disorders.

Lipid Profiling of Pacific Abalone (Haliotis discus hannai) at Different Developmental Stages Using Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectrometry

Pacific abalone (Haliotis discus hannai) is a commercially important mollusk; therefore, improvement of its growth performance and quality has been emphasized. During embryonic development, abalones undergo a series of distinct larval stages, including swimming veliger larvae, juveniles, and mature individuals, and their biomolecular composition varies depending on the developmental stage. Therefore, in the present study, we performed untargeted lipid profiling of abalone tissues at different developmental stages as well as the hemolymph of mature female and male abalones using ultrahigh-performance liquid chromatography-tandem mass spectrometry. These profiles can provide meaningful information to understand compositional changes in lipids through abalone metamorphosis and development. A total of 132 lipids belonging to 15 classes were identified from abalone tissues at different developmental stages. Moreover, 21 lipids belonging to 8 classes were identified from the hemolymph of mature abalones. All data were processed following strict criteria to provide accurate information. Triglycerides and phosphatidylcholines were the major lipid components identified in both tissues and hemolymph, accounting for, respectively, 27% and 15% of all lipids in tissues and, respectively, 24% and 38% of all lipids in the hemolymph. Of note, lysophosphatidylcholine was only detected in the tissues of mature abalones, paving the way for further analyses of abalone lipids based on developmental stages. The present findings offer novel insights into the lipidome of abalone tissues and hemolymph at different developmental stages, building a foundation for improving the efficiency and quality of abalone aquaculture.

Benchmarking One-Phase Lipid Extractions for Plasma Lipidomics

A key element of successful lipidomics analysis is a sufficient extraction of lipid molecules typically by two-phase systems such as chloroform-based Bligh and Dyer (B&D). However, numerous metabolomics and lipidomics studies today apply easy to use one-phase extractions. In this work, quantitative flow injection analysis high-resolution mass spectrometry was applied to benchmark the lipid recovery of popular one-phase extraction methods for human plasma samples. The following organic solvents were investigated: methanol (MeOH), ethanol (EtOH), 2-propanol (IPA), 1-butanol (BuOH), acetonitrile (ACN) and the solvent mixtures BuOH/MeOH (3:1) and MeOH/ACN (1:1). The recovery of polar lysophospholipids was sufficient for all tested solvents. However, nonpolar lipid classes such as triglycerides (TG) and cholesteryl esters (CE) revealed extraction efficiencies less than 5% due to precipitation in polar solvents EtOH, MeOH, MeOH/ACN, and ACN. Sample pellets also contained a substantial amount of phospholipids, for example, more than 75% of total phosphatidylcholine and sphingomyelin for ACN. The loss of lipids by precipitation was directly related to the polarity of solvents and lipid classes. Although, lipid recovery increased with the volume of organic solvent, recovery in polar MeOH remains incomplete also for less polar lipid classes such as ceramides. Addition of stable isotope-labeled internal standards prior to lipid extraction could compensate for insufficient lipid recovery for polar lipid classes including lysolipids and phospholipids but not for nonpolar CE and TG. In summary, application of one-phase extractions should be limited to polar lipid classes unless sufficient recovery/solubility of nonpolar lipids has been demonstrated. The presented data reveal that appropriate lipid extraction efficiency is fundamental to achieve accurate lipid quantification.

HBM4EU Chromates Study: Urinary Metabolomics Study of Workers Exposed to Hexavalent Chromium

Exposure to hexavalent chromium Cr(VI) may occur in several occupational activities, placing workers in many industries at risk for potential related health outcomes. Untargeted metabolomics was applied to investigate changes in metabolic pathways in response to Cr(VI) exposure. We obtained our data from a study population of 220 male workers with exposure to Cr(VI) and 102 male controls from Belgium, Finland, Poland, Portugal and the Netherlands within the HBM4EU Chromates Study. Urinary metabolite profiles were determined using liquid chromatography mass spectrometry, and differences between post-shift exposed workers and controls were analyzed using principal component analysis. Based on the first two principal components, we observed clustering by industrial chromate application, such as welding, chrome plating, and surface treatment, distinct from controls and not explained by smoking status or alcohol use. The changes in the abundancy of excreted metabolites observed in workers reflect fatty acid and monoamine neurotransmitter metabolism, oxidative modifications of amino acid residues, the excessive formation of abnormal amino acid metabolites and changes in steroid and thyrotropin-releasing hormones. The observed responses could also have resulted from work-related factors other than Cr(VI). Further targeted metabolomics studies are needed to better understand the observed modifications and further explore the suitability of urinary metabolites as early indicators of adverse effects associated with exposure to Cr(VI).

Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy

Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests

Metabolomics refers to the large-scale detection, quantification, and analysis of small molecules (metabolites) in biological media. Although metabolomics, alone or combined with other omics data, has already demonstrated its relevance for patient stratification in the frame of research projects and clinical studies, much remains to be done to move this approach to the clinical practice. This is especially true in the perspective of being applied to personalized/precision medicine, which aims at stratifying patients according to their risk of developing diseases, and tailoring medical treatments of patients according to individual characteristics in order to improve their efficacy and limit their toxicity. In this review article, we discuss the main challenges linked to analytical chemistry that need to be addressed to foster the implementation of metabolomics in the clinics and the use of the data produced by this approach in personalized medicine. First of all, there are already well-known issues related to untargeted metabolomics workflows at the levels of data production (lack of standardization), metabolite identification (small proportion of annotated features and identified metabolites), and data processing (from automatic detection of features to multi-omic data integration) that hamper the inter-operability and reusability of metabolomics data. Furthermore, the outputs of metabolomics workflows are complex molecular signatures of few tens of metabolites, often with small abundance variations, and obtained with expensive laboratory equipment. It is thus necessary to simplify these molecular signatures so that they can be produced and used in the field. This last point, which is still poorly addressed by the metabolomics community, may be crucial in a near future with the increased availability of molecular signatures of medical relevance and the increased societal demand for participatory medicine.

Assessment of Biphasic Extraction Methods of Mouse Fecal Metabolites for Liquid Chromatography-Mass Spectrometry-Based Metabolomic Studies

With the increasing knowledge about the important roles of gut microbiota on the biological system, a systematic strategy to profile the fecal metabolome is urgently needed. Thus, an unbiased, efficient, and reproducible fecal metabolite extraction protocol needs to be established; however, the effect of biphasic extraction methods for the fecal samples remains unclear. In this study, five different methods were assessed in the extraction of polar and non-polar metabolites for the liquid chromatography-mass spectrometry (LC-MS)-based mouse fecal metabolomic study. First, the detection coverage of two extraction systems, the Bligh and Dyer extraction method (M1, chloroform/methanol/water, 2/2/1.8) and Matyash method (M2, methyl tert-butyl ether (MTBE)/methanol/water, 10/3/2.5), was compared; then, MTBE/methanol/water system with different solvent ratios (M3, 2.6/2.0/2.4; M4, 4.5/1/2.5; and M5, 3/2.5/2.5) were further evaluated. The results showed that M2 showed higher detection coverage than M1. For the MTBE/methanol/water system with different solvent ratios, M3 showed the largest detection coverage based on peak numbers and numbers of putatively annotated metabolites, while M4 presented the least overlap between two phases, higher peak intensities of metabolites, and superior reproducibility. Based on the above evidence, M4 was recommended for the biphasic extraction of fecal metabolites in the LC-MS-based mouse fecal metabolomic study.

Characterization of Monophasic Solvent-Based Tissue Extractions for the Detection of Polar Metabolites and Lipids Applying Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry Clinical Metabolic Phenotyping Assays

Metabolic phenotyping of tissues uses metabolomics and lipidomics to measure the relative polar and nonpolar (lipid) metabolite levels in biological samples. This approach aims to understand disease biochemistry and identify biochemical markers of disease. Sample preparation methods must be reproducible, sensitive (high metabolite and lipid yield), and ideally rapid. We evaluated three biphasic methods for polar and nonpolar compound extraction (chloroform/methanol/water, dichloromethane/methanol/water, and methyl tert-butyl ether [MTBE]/methanol/water), a monophasic method for polar compound extraction (acetonitrile/methanol/water), and a monophasic method for nonpolar compound extraction (isopropanol/water). All methods were applied to mammalian heart, kidney, and liver tissues. Polar extracts were analyzed by hydrophilic interaction chromatography (HILIC) ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS) and nonpolar extracts by C₁₈ reversed-phase UHPLC-MS. Method reproducibility and yield were assessed using multiple annotated endogenous compounds (putatively and MS/MS annotated). Monophasic methods had the highest yield and high reproducibility for both polar (positive ion: median relative standard deviation (RSD) < 18%; negative ion: median RSD < 28%) and nonpolar (positive and negative ion: median RSD < 15%) extractions for heart, kidneys, and liver. The polar monophasic method extracted higher levels of lipid than biphasic polar extractions, and these lipids caused minimal detection suppression for other compounds during HILIC UHPLC-MS. The nonpolar monophasic method had similar or greater detection responses of all detected lipid classes compared to biphasic methods (including increased phosphatidylinositol, phosphatidylserine, and cardiolipin responses). Monophasic methods are quicker and simpler than biphasic methods and are therefore most suited for future automation.